In an alarming study last month, researchers found that 65 percent of baby food tested positive for unsafe levels of arsenic and nearly 36 percent for lead. Unsurprisingly, this study has sent shockwaves through the parenting community and baby food industry.
In response, a slew of startups have launched to bring new alternatives to an industry still dominated by big three corporates (Gerber -- a Nestle subsidiary, Plum Organics -- a Campbell's subsidiary, and Happy Baby -- a Danone subsidiary). The common theme among these new startups is a promise to provide high-quality, freshly made baby food, and from some of the brands, the added convenience of direct-to-your-door delivery. I've seen this trend take off across other food and beverage categories, such as Gobble, Freshly, and even dog food with startups like Mosi.
But the founders of Little Spoon, whom I met through Kairos, are adding an extra layer to new solutions: personalizing baby food to meet each child's unique health needs. Little Spoon first learns about your child through a short questionnaire. It then creates a personalized meal-plan to ensure that each baby gets the right nutrients at the right stage of their development. And then Little Spoon delivers custom, freshly made meals direct to parents' doors each week. It's a model we've seen with other health and wellness companies, but it's the first I've seen in the baby food space.
Scaling a startup with that level of personalization isn't easy. Today, Little Spoon is available in all 50 states. I asked their team to share some insights on how other entrepreneurs can build a personalized service that scales. I learned three strategies from our conversation:
1. Focus on 4-5 key attributes.
Rather than trying to make each item customized from the ground up, pick a subset of attributes that you personalize against. For Little Spoon, this includes factors like the babies age, eating style, and core nutrient requirements.
A good start for any entrepreneur is to ensure you truly understanding the problem you are solving and what matters most to your customer. Why would one customer's needs differ than another's? This will give you a solid initial list of attributes or variables to work with.
2. Design products that index on each attribute.
Map out the set of attributes or variables that your offering needs to hit on, and figure out the minimum amount of variation needed. For Little Spoon, they were able to create 25 different meals that hit on the key nutrients, textures, and flavors babies need throughout their development.
Depending on your product, you can may be able to create hundreds of different varieties, but you likely won't need to invest in them all. Figure out what the bare minimum varieties you need to service the full set of customer attributes you mapped out. For a clothing company, it may be critical at bare minimum to have five sizes from XS to XL, but less critical to have that much variation for other attributes (like colors, designs, or materials).
3. Personalize through combinations, not individual products.
It's easier to achieve personalization at scale by mixing and matching individual products to the unique user's overall need, rather than trying to personalize each specific item. Little Spoon looks at what the baby needs nutritionally for each shipment, then selects the mix of blends that hit on those combinations of nutrients. The selection of blends, quantity of each, and timing of when they introduce specific flavor and texture combinations are all levers they pull to personalize the shipment.
Care/of customers are obsessed with their personalized daily vitamin packs, Stitch Fix's personalized clothing boxes hit the mark despite not tailoring individual items, and Hawthorne uses body chemistry and lifestyle data to tailor a perfect cologne. I see this combination strategy working very well across a variety of industries and strongly believe that this is the future of e-commerce.
Learn more about other Kairos companies and young industry disruptors with the Top 30 Emerging Companies of 2017.